Dual-Mode Fluorescent/Intelligent Lateral Flow Immunoassay Based on Machine Learning Algorithm for Ultrasensitive Analysis of Chloroacetamide Herbicides

Abstract Given the harmful effect of herbicide residues, it is essential to develop portable and accurate biosensor for the analysis of herbicides in the environment and agricultural products. In this paper, we demonstrated a dual mode lateral flow immunoassay (LFIA) for rapid and sensitive detection of chloroacetamide herbicides, which utilizes a horseradish peroxidase (HRP)-IgG conjugated time-resolved fluorescent nanoparticle (TRFNP) probe as both signal label and amplification tool. With the newly developed LFIA, the limits of detection (LODs) were 0.08 ng/mL of acetochlor (ATC), 0.29 ng/mL of metolachlor, 0.51 ng/mL of propisochlor, and 0.13 ng/mL of their mixture in fluorescent mode and 0.39 ng/mL of ATC, 0.75 ng/mL of metolachlor, propisochlor, and their mixture in colorimetric mode. Importantly, the practical applicability was successfully demonstrated by determining ATC in corn sample with good recovery rates (97.12–111.46%) that correlate well with commercial enzyme linked immunosorbent assay (ELISA) kit. The proposed LFIA acquires broadened detection range (0.20–200 ng/mL), reduced detection time (12 min), excellent sensitivity, portability, repeatability and reliability by implementing a dual mode strategy, indicating promising potential as a tool for pesticides detection.